題 目：Stableimage restoration by TV type methods
内容簡介：Somenew TV type minimization models are introduced to investigate robustimage recovery from a certain number of noisy measurements by theproposed TV type minimization models. Error bounds of robust imagerecovery from compressed measurements via the proposed minimizationmodels are established, and the RIP based condition is improvedcompared with total variation (TV) minimization. Numerical results ofimage reconstruction demonstrate our theoretical results andillustrate the efficiency of the proposed TV type minimization modelsamong state of-the-art methods.
報告人：谌穩固
報告人簡介：北京應用物理與計算數學研究所研究員，博士生導師，主要從事調和分析、壓縮感知、機器學習、大數據分析的理論及應用研究，在IEEETransactions on Information Theory, Applied and ComputationalHarmonic Analysis，InverseProblems, SIAM Journal on Imaging Sciences, Journal of MachineLearning等學術期刊發表科研論文70餘篇。
時 間：2023年11月17日（周五）上午9：00開始
地 點：騰訊會議：184-215-195
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